Epidemiological evidence is regularly presented to courts in
determining proof of causation in medicinal product liability
litigation. Building on the foundations of the author's previous
monograph, which supported the use of epidemiological evidence in
dealing with problems of proof of causation in alleged cases of adverse
drug reactions, this paper revisits this perennial problem of the role
of epidemiological evidence in assessing causation in product liability
cases in a twenty-first century context, examining recent cases in the
United Kingdom, United States, Australia, and Canada. It seeks to
determine the extent to which the courts in the highlighted cases have
been pragmatic and fair in their interpretation and utilization of
epidemiological evidence, from the perspective of both consumers and
pharmaceutical manufacturers. The paper examines the apparent tension
between the levels of proof required in law and science, including the
relationship between levels of statistical significance and the
claimant's burden of proof; and it assesses the wisdom of using a
doubling of the risk rule as a threshold to any recovery. It explores
the ways in which probabilistic methods, including statistical refining
with individual risk factors, can be used in conjunction with
epidemiological evidence to determine specific causation. The paper
supports the view that logistic regression techniques and other forms of
statistical refining mechanisms using specific risk factors can and do
help in the process of giving quantitative or quasi-quantitative
expression to conclusions about the cause of disease in an individual
drug product liability claim that is based on epidemiological evidence.

Introduction
I. Reconciling the Standards of Proof in Law and
Science in the United Kingdom
A. Evidence of Causation for Purposes of Science
and for Purposes of Law
B. Doubling of Risk Theory
C. Association Versus Causation
D. Teaching Courts Epidemiology
E. The Statistical Chance/Personal Chance Dichotomy
F. Overcoming the Statistical Chance/Personal
Chance Dichotomy: Statistical Refuting Mechanisms
Using Specific Risk Factors
Conclusions

Introduction

Proof of causation in toxic tort litigation is an inherently
difficult problem, which regularly requires time-consuming analysis of
complex scientific evidence. (1) The difficulties in proving both
general causation (whether a product was capable of causing the damage
alleged) and specific causation (whether the product did so in the
individual case) are magnified in the context of medicinal products. (2)
As Harvey Teff and Colin Munro have highlighted:

Drugs are always potentially dangerous due to their toxicity. They
are often taken by people who are already ill and who may be
unusually susceptible to further ailments. Unlike many other
products, they may cause injury in unpredictable ways, depending on
the individual user's constitution. They may not be taken according
to the instructions. The user may be allergic to a particular drug.
Alternatively, what appears to be an allergy may in fact be a toxic
reaction. (3)

With a multitude of new kinds of drugs emerging as a harvest of the
scientific and technological revolutions of both the twentieth and early
twenty-first centuries, the cases have become even more complex,
demanding much from lawyers and scientific experts on both sides and
from judges themselves. (4)

The practical significance of establishing causation in a medicinal
product liability case cannot be overstated. In the United Kingdom,
whether the claim is in negligence or under the strict liability
provisions of the Product Liability Directive, (5) proof of causation
will often lead to either a settlement or a successful claim. (6)
Conversely, a failure to establish a causal link between a medicinal
product and, for example, the alleged medical conditions of claimants,
may lead to such claims being struck out as an abuse of the process of
the court on the basis that each claim has no real prospect of success.
(7)

Epidemiology is defined as "the field of public health and
medicine that studies the incidence, distribution and etiology of
disease in human populations." (8) Epidemiological evidence is
regularly presented to courts in determining proof of causation in
medicinal product liability litigation. Building on the foundations of
the author's previous monograph, which supported the use of
epidemiological evidence in dealing with problems of proof of causation
in alleged cases of adverse drug reactions, (9) this paper revisits the
perennial problem of the role of epidemiological evidence in assessing
causation in product liability cases in a twenty-first century context,
examining recent cases in the United Kingdom, United States, Australia,
and Canada. In essence, it seeks to determine the extent to which the
courts in the highlighted cases have been pragmatic and fair in their
interpretation and utilization of epidemiological evidence, from the
perspective of both consumers and pharmaceutical manufacturers.

In order to establish factual causation in the context of medicinal
product liability, claimants must prove both general causation
("whether a substance is capable of causing a particular injury or
condition in the general population") (10) and specific causation
("whether a substance caused a particular individual's
injury"). (11) Since epidemiology is based on the study of
populations and not individuals, it focuses on the question of general
causation rather than specific causation. (12) Epidemiological evidence
may identify an association between a drug and a disease, but whether
such an association is causal requires an evaluation of the evidence,
with emphasis on the extent to which weaknesses of a study's design
and implementation compromise its findings and inferences about
causation. (13)

The results of epidemiological studies cannot per se conclusively
prove specific causation. However, several cases have focused on the
role that epidemiological evidence plays in determining proof of
specific causation, which is a legal question addressed by courts. (14)
This paper explores the ways in which probabilistic methods, including
statistical refining with individual risk factors, can be used in
conjunction with epidemiological evidence to determine specific
causation.

Part IA explores the apparent tension between the levels of proof
required in law and science, including the relationship between levels
of statistical significance and the claimant's burden of proof.
Part IB assesses the wisdom of using a "doubling of the risk"
rule as a threshold to any recovery. Notwithstanding the problems with
the doubling of risk theory in the United States, its usage appears to
be gaining ground in the United Kingdom. Moreover, in particular, the
doubling of risk theory has come to recent attention in the context of
the utilization and value of epidemiological or statistical evidence
alone in determining causation on a balance of probabilities, with
discussion by the UK Supreme Court in Sienkiewicz v. Greif. (15)
cautious attitude toward the use of the doubling of risk rule in the
context of both general and specific causation is seen from the case law
explored. In examining the distinction between association and
causation, Part IC discerns two main reasons for this judicial
scepticism about epidemiological evidence, namely the propriety of
drawing causal inferences from observed associations (a general
causation issue) and the propriety of drawing causal inferences in
individual cases from concededly causal associations observed in samples
of populations (a specific causation issue). These reasons are discussed
in an analysis of the controversial Scottish case of McTear v. Imperial
Tobacco Ltd (16) and the decision of the Federal Full Court of Australia
in Merck Sharp & Dohme (Australia) Pty Ltd v. Peterson. (17) In the
context of McTear, Part ID discusses the necessity of requiring
something more than a doubling of the risk to permit the claimant to
recover, and it stresses the role of judges in resolving this issue.

Part IE discusses the implications for specific causation, in the
context of McTear, of epidemiology being based on the study of
populations and not individuals. It suggests that the limitations of
epidemiological evidence in determining specific causation as described
by the trial judge are somewhat inaccurate since, in establishing
specific causation, epidemiologists can and do adjust for potentially
confounding factors through logistic regression techniques and other
forms of statistical refining mechanisms. Part IF therefore concludes
with an examination of such statistical refining methods in determining
specific causation in medicinal product liability cases, including the
use of Bayes' theorem to help us understand how statistical risks
can be refined using personal risk factors. The paper does not argue
that Bayes' theorem is necessarily the answer to the problem of
establishing specific causation in the context of epidemiological
evidence. Nonetheless, while recognizing the limitations of Bayes'
theorem, the paper supports the view that logistic regression techniques
and other forms of statistical refining mechanisms using specific risk
factors can and do help in the process of giving quantitative or
quasi-quantitative expression to conclusions about the cause of disease
in an individual drug product liability claim that is based on
epidemiological evidence. Finally, the paper illustrates the increasing
support for the refining and personalizing of epidemiological evidence
in cases of individual causation involving medicinal products, as
evidenced by the decision of the Ontario Superior Court of Justice in
Andersen u. St Jude. (18)

I. Reconciling the Standards of Proof in Law and Science in the
United Kingdom

A. Evidence of Causation for Purposes of Science and for Purposes
of Law

There is an apparent tension between the levels of proof required
in law and in science. For the law of negligence, it is sufficient to
show that the balance of probabilities--meaning more than fifty per
cent, or on a preponderance of the evidence--indicates a causal
connection. It is sometimes erroneously assumed by lawyers that
scientists regard an association as causal if it is ninety-five per cent
certain. (19) However, this is a misinterpretation of the so-called p
value, which is merely the level of statistical significance used to
exclude the possibility that when something transpires in a cohort of
cases, it does so by chance (i.e., the null hypothesis). When the p
value falls below the threshold of 0.05, the investigator is able to
reject the null hypothesis since there is a less than one in twenty
chance that the link between exposure and disease is random. (20) While
there is no generally accepted standard of scientific proof for
causation, (21) and neither the claimant nor the defendant is required
to apply scientific standards of proof when determining causation on a
balance of probabilities, (22) such a standard must be "much more
than marginal". (23) In light of this apparent tension between the
balance of probabilities standard and the standard of statistical
significance, courts must be alert to the problem that may be faced by
an expert "in readjusting his focus from the ninety-five per cent
confidence limit approach to the balance of probabilities test."
(24) However, in Vadera v. Shaw (25) the English Court of Appeal
reconciled the legal standard of proof on a balance of probabilities
with the scientific standard of statistical significance, in holding
that a failure to establish a statistically significant connection
between the oral contraceptive Logynon and the occurrence of strokes was
fatal to the establishment of proof of causation on a balance of
probabilities. Lord Justice Henry stated:

The judge concluded, and in our respectful view was right on the
evidence to conclude, that the studies carried out and referred to
by Dr Lidegaard [for the plaintiff] did not establish a
statistically significant connection between Logynon and strokes.
Such evidence cannot be ignored by a judge. It is as common sense a
conclusion as one could wish to say that if the connection between
A and B cannot be shown with confidence to be other than a
coincidence, then it cannot be held on a balance of probabilities
that A caused B. This is not to allow scientists or statisticians
to usurp the judge's function, but rather to permit him to use
their skills to discern a connection, or a lack of connection,
between two phenomena. (26)

B. Doubling of Risk Theory

Epidemiologists investigating disease causation measure the
association between exposure to an agent and the incidence of disease by
using the concept of relative risk. Relative risk is defined as the
ratio of the incidence of a disease in a population exposed to the agent
to the incidence of disease in a population that has not been exposed.
(27) For example, if ten per cent of all people exposed to a drug
develop a disease, compared with five per cent of people who are
unexposed, the disease occurs twice as frequently among the exposed
people. The relative risk is ten per cent/five per cent (i.e., two). A
relative risk of one shows no association between exposure and disease.
(28)

A significant attempt to reconcile the apparent tension between the
balance of probabilities standard and the standard for epidemiology has
emerged with the theory that causation can be proven on the balance of
probabilities by reference to the doubling of risk of injury theory.
That theory has long been recognized in the United States, (29) where it
has been said that "[t]he use of scientifically reliable
epidemiological studies and the requirement of more than a doubling of
the risk strikes a balance between the needs of our legal system and the
limits of science." (30) However, the theory has also been subject
to trenchant criticism. (31) In particular, academics have argued that
judges have adopted "substantive changes in causation law through
the rubric of evidentiary admissibility decisions" (32) and
"have frequently conflated admissibility decisions and sufficiency
of evidence decisions." (33) Those courts which require plaintiffs
to produce epidemiological studies with a relative risk of two are
making a "legal policy determination to equate epidemiology,
relative risk, general causation, and the burden of proof on individual
causation." (34) Moreover, while the total number of judicial
opinions that at least mention the concept of doubling of risk has
increased, US courts disagree as to the proper role of the doubling of
risk theory in deciding questions of both sufficiency and admissibility
of scientific evidence of causation in toxic tort cases. They do not
agree on whether to adopt the doubling of risk as a threshold, nor do
they agree on the meaning of such a threshold. (35) As the reporters for
the American Law Institute's Restatement Third of Torts have noted:

Many courts accept the doubling of the incidence of disease in
group studies; some courts insist on doubling of risk as a minimum
threshold for establishing specific causation. Others have
recognised that if other known causes can be identified and
eliminated, something less than a doubling would still be
sufficient to find specific causation. (36)

Accordingly, the requirement of a relative risk of two for the
admissibility or sufficiency of epidemiological evidence has been
subject to much scepticism. (37) The reporters for the Restatement Third
of Torts, in discussing the considerations that affect the
appropriateness of determining the probability of specific causation
based on the outcome of group studies, have concluded that a judicial
requirement that plaintiffs show a threshold increase in risk (or a
doubling of incidence in a group study) to satisfy the burden of proof
of specific causation is "usually inappropriate". (38)

Notwithstanding the problems with the doubling of risk theory in
the United States, its existence appears to be gaining ground in the
United Kingdom. Of particular significance was the case XYZ v. Schering
Health Care Ltd, (39) a trial of seven lead cases in group litigation
against three pharmaceutical companies in respect of cardiovascular
injuries coming under the collective description of venous
thromboembolism (VTE). The claimants alleged that their injuries were
caused by taking the defendants' different brands of
third-generation combined oral contraceptives. The claimants alleged
that the products they took were defective under the Consumer Protection
Act 1987 and the Product Liability Directive. While the cause of action
was based on strict liability, the requirement common to both negligence
and strict liability of proving a causal link between the product and
the damage (i.e., the issue of general causation) emerged as the first
central issue requiring determination.

Justice Mackay stated that the claimant could prove that an
exposure to risk caused injury if that exposure had more than doubled
the risk of the injury occurring. (40) This method of proving causation
had previously been applied in a case of bladder cancer, where the
claimant had been tortiously exposed to carcinogens and non-tortiously
exposed to cigarette smoke, both of which are potent causes of the
condition. (41) However, it has been argued that since the doubling of
risk approach is only valid where the risk estimate represents
"mutually exclusive ways in which the injury may have been
caused" and is sought "to estimate the likelihood it was one
way which had operated in a particular case rather than one of the other
possible ways." (42) As such, the doubling of risk approach is not
validly applicable as a method to cases of bladder cancer, where the
mechanism by which an agent (e.g., amines) present in two sources (e.g.,
occupational amine exposure and amines contained in cigarette smoke)
causes bladder cancer is unknown. (43) By contrast, such comparisons of
risk estimates in the doubling of risk approach would be statistically
valid where the estimates relate to mechanisms which, even if their
details are not understood, are known to involve different agents, such
as a birth defect that may be attributable either to a medicinal product
or to a background risk. (44)

"The utilization and value of epidemiological or statistical
evidence alone in determining causation on a balance of probabilities
was subject to some interesting debate in the [UK] Supreme Court in
Sienkiewicz v. Greif." (45) The reason for this discussion, as
pointed out by Baroness Hale, (46) was the presence of an obiter
observation by Lady Justice Smith in her judgment in Sienkiewicz that
"in a case of multiple potential causes, a claimant can demonstrate
causation by showing that the tortious exposure has at least doubled the
risk arising from the non-tortious cause or causes." (47) Their
Lordships were postulating the scenario where, having established
general causation between the toxic agent and the disease,
epidemiological evidence might be used to establish specific causation.
While their Lordships held unanimously that there was no room for
introducing the doubling of risk approach to "single exposure"
(48) mesothelioma cases or multiple defendant mesothelioma cases, (49)
differences in view emerged with the obiter discussion of the general
applicability of the doubling of risk theory using epidemiological
evidence to determine proof of causation in personal injury cases.

Lord Phillips discussed the XYZ decision and took the view that,
while the case contained "a detailed and illuminating discussion of
epidemiology," it did not afford any direct assistance to the
question whether the "doubles the risk" test--as he called
it--was appropriate for determining causation in a case of multiple
potential causes. (50) His reasoning was somewhat obscured by his
misclassification of the contraceptives in this case. He stated that the
issue "was whether a second generation of oral contraceptives more
than doubled the risk of causing deep vein thrombosis (DVT) that was
created by the first generation of contraceptives ... It was not whether
the DVT suffered by the claimants had been caused by the second
generation of oral contraceptives." (51)

In fact, the issue was whether the claimants had proved that third
generation combined oral contraceptives caused a true excess risk of
VTE, which was more than twice the risk caused by second generation
combined oral contraceptives. Both sides in XYZ agreed that if the
claimants failed to prove this, the action could not succeed. However,
both parties had also agreed that if the claimants could prove a true
excess risk of VTE, they would also succeed on the second issue, which
was whether the relevant products were defective within the meaning of
section 3 of the Consumer Protection Act 1987 (i.e., that their safety
would not be such as persons generally were entitled to expect) (52).
The test of defectiveness under section 3 (2) (a) of the Act includes
consideration of instructions or warnings associated with the product.
Thus, the reasoning behind the doubling of risk theory's relevance
to establishing that the third generation contraceptives were defective
was that if the UK Supreme Court ruled that the true risk of VTE was
more than doubled with third generation combined oral contraceptives,
women and their prescribers were entitled to be told this before making
their decisions or giving their advice, respectively--and they had not
been. (53)

Lord Phillips' reasoning seems to ignore the fact that
causation was inherently behind the court's approach. As Justice
Mackay explained in XYZ:

The reason why the Claimants accept, through Lord Brennan QC, that
this first issue is capable of disposing of the claims should be
set out. It is not because an increase of less than two would fail
to render the product defective within the meaning of the Act,
though the Defendants would so argue if they had to. It is for
reasons of causation that he accepts this burden, correctly in my
view. If factor X increases the risk of condition Y by more than
two when compared with factor Z, it can then be said, of a group of
say 100 with both exposure to factor X and the condition, that as a
matter of probability more than 50 would not have suffered Y
without being exposed to X. If medical science cannot identify the
members of the group who would and who would not have suffered Y,
it can nevertheless be said of each member that she was more likely
than not to have avoided Y had she not been exposed to X [emphasis
added]. (54)

While Lord Phillips concluded (55) that there was no scope for the
doubling the risk test in cases where two agents operated cumulatively
and simultaneously in causing the onset of a disease, since in such
cases the material contribution rule in Bonnington Castings v. Wardlaw
(56) would apply, he submitted (57) that there was no reason in
principle why the "doubles the risk test" should not be
applied where the initiation of a disease was dose-related and there had
been consecutive exposures to an agent or agents that cause the disease
(e.g., McGhee v. National Coal Board). (58) Lord Phillips regarded
Hotson v. East Berks Area Health Authority (59) as an example of the
latter situation. (60)

However, neither Lord Rodger nor Baroness Hale took such a view,
both holding that a doubling of risk approach was not an appropriate
test of causation. (61) Lord Rodger stressed that where statistical
evidence established that exposure to a substance more than doubled the
risk of a disease, this would not amount to proof, on the balance of
probabilities, that the exposure actually caused the disease. (62)
Meanwhile, Lord Dyson did not "find it necessary to decide whether
there are any circumstances in which, as a matter of English law,
causation can be proved on the basis of epidemiological evidence
alone." (63) He expressed the view that "there [was] no a
priori reason why, if the epidemiological evidence [was] cogent enough,
it should not be sufficient to enable a claimant to prove his case
without more." (64) By contrast, Lord Kerr stressed the need to
treat the use of epidemiological evidence to seek to establish any
specific proposition in an individual case with great caution. (65) He
felt that there was a real danger that "so-called
'epidemiological evidence' [would] carry a false air of
authority." (66)

Finally, Lord Mance felt that whether and when epidemiological
evidence could prove a case was "a question best considered not in
the abstract but in a particular case, when and if that question
[arises]." (67) If it could arise, he would hope and expect that
this would only occur in the rarest of cases. (68)

This cautious attitude toward the use of the doubling of risk rule
in the context of specific causation has been reflected in medicinal
product liability litigation concerning the anti-inflammatory drug
Vioxx. In Merck Sharp & Dohme (Australia) Pty Ltd v. Peterson, (69)
plaintiffs alleged in representative proceedings that consumption of
Vioxx increased the risk of a myocardial infarction (heart attack) and
that Vioxx had caused or contributed to the myocardial infarction of the
class representative, Mr. Peterson. (70) The trial judge, Justice
Jessup, had held that the epidemiological evidence had demonstrated that
Vioxx had doubled the risk of heart attack across the population as a
whole, (71) and that consumption of Vioxx materially contributed to
Peterson's heart attack. (72) Yet in upholding Merck
Australia's appeal on the issue of causation, the Full Court
criticized the doubling of risk approach as being "apt to mandate
an award of compensation to applicants who have not, in truth, been
injured by the respondent." (73) It also noted that, while a
relative risk of two might imply a fifty per cent probability that the
risk had been realized in a typical case, a relative risk of less than
two would imply a probability of less than fifty per cent. The trial
judge's finding of relative risk had been "about two".
(74)

C. Association Versus Causation

It is arguable that it would be an oversimplification to think that
the views of Lord Phillips in Sienkiewicz will help to signal a green
light to the establishment of proof of causation on a balance of
probabilities by a mere doubling of relative risk. The matter was
addressed in Merrell Dow Pharmaceuticals, Inc. v. Havner (75) where,
having stated that a balance between the needs of the legal system and
the limits of science could be achieved by the use of scientifically
reliable epidemiological studies and the requirement of more than
doubling the risk, the Supreme Court of Texas added the caveat:

We do not hold, however that a relative risk of more than 2.0 is a
litmus test or that a single epidemiological test is legally
sufficient evidence of causation. Other factors must be considered.
As already noted, epidemiological studies only show an association.
There may in fact be no causal relationship even if the relative
risk is high. (76)

The latter sentence is of particular importance, and while Lord
Phillips in Sienkiewicz referred to the caveat expressed in Havner, (77)
he omitted that last sentence and ignored its import in his final
analysis. Unlike Lord Phillips, Lord Rodger stressed the importance of
the distinction between association and causation. In this context, Lord
Rodger's reason for scepticism about epidemiological evidence
concerns the propriety of drawing causal inferences from observed
associations (a general causation issue); yet there is seemingly a
further reason for scepticism in his speech, regarding the propriety of
drawing causal inferences in individual cases from concededly causal
associations observed in samples of populations (a specific causation
issue). (78) Lord Rodger's speech is more compelling in that it
shows a greater understanding of both the significance and the
limitations of epidemiological evidence, and it demonstrates a
reluctance to support the general application of the doubling of risk
theory to determining proof of both general and specific causation in
personal injury cases. (79) Lord Rodger accepted that epidemiological
and statistical evidence may form an important element in proof of
causation, and he supported the utilization and value of epidemiological
evidence where a claimant was required to prove his case on a balance of
probabilities. (80) However, he emphasized that, since by its very
nature statistical evidence does not deal with the individual case, the
court should not proceed to find a causal relationship in that
particular case without further non-statistical evidence (e.g., evidence
of temporality of the appearance of results of the exposure). (81) In so
doing, he cited Phipson on Evidence, which states that "[w]here
there is epidemiological evidence of association, the court should not
proceed to find a causal relationship without further, non-statistical
evidence." (82) Lord Rodger illustrated his example of evidence of
temporality in the context of a medicinal product and an adverse effect,
where there was "a strong epidemiological association between a
drug and some condition that could have been caused in some other
way." (83) He submitted that epidemiological evidence, "along
with evidence that the claimant developed the condition immediately
after taking the drug," could be sufficient to allow the judge to
conclude that the drug caused the condition on the balance of
probability. (84)

The Federal Full Court of Australia's decision in Peterson is
another example of courts' reluctance to draw inferences from a
population to an individual in the context of medicinal products. (85)
There the Full Court upheld the "but for" test of causation
and found that the trial judge's findings of fact were insufficient
to sustain the position that, on the balance of probabilities, but for
the consumption of Vioxx, Peterson's myocardial infarction would
not have occurred. (86) The court concluded that while the
epidemiological evidence meant that it was possible Vioxx had caused
Peterson's myocardial infarction, there were other strong potential
causes, such as "age, gender, hypertension, hyperlipidaemia,
obesity, left ventricular hypertrophy and [a] history of smoking."
(87) Peterson was therefore "a member of a group within the
community, 25% of whom were expected by ... cardiologists to suffer a
heart attack within 5 years." (88) These personal circumstances
seriously diminished the strength of the epidemiological evidence as a
strand in the cable of circumstantial proof. (89) Accordingly, the Full
Court held that it was not more probable than not that Vioxx, whether
alone or in combination with Peterson's personal risk factors, was
a necessary condition of the occurrence of his heart attack. (90) While
a relative risk of two could be converted into a fifty per cent
statistical likelihood that Vioxx was causally implicated in the
occurrence of a myocardial infarction, there were other candidates as
causes of the injury. The strength of the epidemiological strand did not
rise above the possibility that it was "in the mix" of factors
which may have caused Peterson's heart attack. (91) While the fact
that the plaintiff in Peterson suffered from several personal risk
factors prima facie cuts against recovery, this mere fact alone does not
resolve the import of the epidemiological evidence. The difficulty lies
with the fact that epidemiological evidence conflates people with
different underlying conditions, and it may not be known what the
relative risk is for those individuals with no history of heart disease
compared to individuals, such as Peterson, with a long history of heart
disease. Indeed, there is a strong argument, based on Merck's own
VIGOR study of Vioxx, that the relative risk of taking Vioxx is equally
strong in both subgroups and that Vioxx could have caused a heart attack
even in someone with a history of heart disease. (92) There is thus no
data to support the Full Court's conclusion that personal
circumstances seriously diminish the strength of the epidemiological
evidence. Accordingly, the court's approach was arguably a guess by
a sceptical court that Vioxx is incapable of being identically
implicated both in cases of individuals with preexisting heart problems
and in cases of those without.

In light of Lord Rodger's observations in Sienkiewicz, and
from the perspective of the propriety of drawing causal inferences from
observed associations, the mere existence of a statistically significant
association is insufficient to establish a causal relationship without
the presence of further non-statistical evidence. To establish a causal
relationship, factors such as those enumerated by Sir Austin Bradford
Hill would need to be utilized to determine whether a reported
association is causal. (93) This point was emphasized by the Scottish
Court of Session in McTear u. Imperial Tobacco Ltd, (94) a decision
which takes a cautious approach to the use of epidemiological evidence
and stresses the impossibility of applying epidemiological studies to
determine causation in individual cases. The case illustrates the
court's scepticism about the epidemiological evidence, as the court
questioned the propriety of drawing causal inferences from observed
associations when determining general causation. The court was also
sceptical about the propriety of drawing causal inferences in individual
cases from causal associations observed in samples of populations. While
this case concerns tobacco products, its implications are particularly
pertinent to problems involving medicinal products, where the role of
epidemiological evidence in proving both general and specific causation
is prominent.

UK developments in this area have often focused on the difficulty
in proving general and specific causation using epidemiological evidence
(95) derived from trends in general populations. This was graphically
illustrated by McTear. In that case, the pursuer, the widow of a smoker,
sought to recover damages from the defenders, who had manufactured the
John Player brand cigarettes that the pursuer's late husband had
smoked. The pursuer's husband had contracted squamous cell
carcinoma of the lung, and the pursuer averred both that cigarette
smoking could cause lung cancer (an issue of general causation) and that
her husband's lung cancer was caused by his smoking (an issue of
individual or specific causation).

The problem of establishing a general causal link between cigarette
smoking and cancer was exacerbated by the fact that, unlike all the
cigarette companies in the United States and all the other cigarette
companies in the United Kingdom, Imperial Tobacco had not accepted that
there was a causal link between smoking and disease, especially lung
cancer. (96) In respect of establishing general causation, Lord Nimmo
Smith concluded that, in the absence of such an admission, and indeed of
any evidence that this was an inference that should be drawn, the burden
of proof lay on the pursuer to show that cigarette smoking could cause
lung cancer. (97) In the absence of support from animal experiments,
proof of causation between cigarette smoking and lung cancer depended on
what was proven before the court about epidemiological studies.

Lord Nimmo Smith held that, in accordance with the Scots law of
expert evidence, it was necessary to consider whether the evidence of
any expert witness had imparted to the court special knowledge of the
subject matter of epidemiology so as to enable the court to draw its own
conclusions from epidemiological evidence. Accordingly, it was not open
to the court to form its judgment on the evidence without being taught
how to analyze the epidemiological evidence to a sufficient extent, and
without being provided with sufficient factual material to enable proof
on the balance of probabilities not only that there was an association
between cigarette smoking and lung cancer, but also that the proper
conclusion to be drawn from this was that there was a causal connection
between them. (98) This distinction between association and causation in
the context of the general causation issue lay at the heart of Lord
Nimmo Smith's conclusions. In his view, when an association between
an exposure and a condition was judged to be statistically significant,
that in itself did not constitute a judgment that there was a causal
connection between an exposure and a condition. (99) He explained:

The finding of an association between an exposure and a condition
or disease, even if judged to be statistically significant, does
not of itself connote that a causal connection between the two is
established. This is a matter for further exercise of judgment,
taking account of such criteria as the consistency, the strength,
the specificity, the temporal relationship and the coherence of the
association ... This must, I think, especially be so when, in the
view of Sir Richard Doll ... cigarette smoking is not a necessary
cause nor a sufficient cause of lung cancer[.] (100)

Lord Nimmo Smith then addressed the concept of relative risk,
concluding that even a relative risk derived from comparison of the
incidence of lung cancer in smokers and non-smokers, of a magnitude such
that a positive association may be judged to be strong enough to
establish causation between the two, did not connote the establishment
of a causal link. (101)

As we shall now see, this scepticism about epidemiological evidence
and questions about the propriety of drawing causal inferences from
observed associations was not the only problem that the pursuer had in
establishing general causation in McTear. The court also had to be
taught the relevant epidemiology.

D. Teaching Courts Epidemiology

In respect of general causation, Lord Nimmo Smith held that the
pursuer had failed to prove, in accordance with the requirements of the
Scots law of evidence relating to expert witnesses, that cigarette
smoking could cause lung cancer. (102) This was because the pursuer had
failed to lead sufficient evidence, in the form of primary
epidemiological literature that drew a causal connection between
cigarette smoking and lung cancer, to impart to the court special
knowledge of the subject matter so as to enable the court to form its
own judgment about it and the conclusions to be drawn from it. (103)
Lord Nimmo Smith stated that "a fundamental defect in the
presentation of the pursuer's case" was the failure to present
in court any of the primary literature that had concluded that there was
a causal connection between cigarette smoking and lung cancer. (104) In
his view, this was a missed opportunity:

This could have been done: it is clear that the survey of British
doctors, on which Sir Richard Doll and colleagues have worked for
many years, is regarded as a classic of its kind, both because of
the pioneering nature of the research, a preliminary report of
which was published as Doll and Hill (1950), and because this has
been followed up with subsequent papers over several decades. I
could at least have been shown these papers, which I assume
disclosed the data, the statistical techniques and all the other
considerations which led to the authors' conclusions, so that I
could see for myself whether these conclusions were soundly based.
The opportunity was there, with Sir Richard Doll in the witness
box, and indeed Processor] Friend for one thought that evidence
would be given about this survey. Warning had been given on behalf
of [Imperial Tobacco Ltd] ... that Sir Richard Doll's data were of
potential interest to the court. But in the event no attempt was
made to show me the data. (105)

A recent Scottish case, Smith v. McNair, (106) reaffirms this
cautious approach to the interpretation of epidemiological evidence.
(107) It stresses the need for experts to teach a court how to analyze
epidemiological evidence before it can come to a judgment by
interpreting that evidence. While acknowledging that medical witnesses
are entitled to refer to medical literature--in particular to published
papers by epidemiologists--even if they themselves are not
epidemiologists, (108) Lord McEwan in McNair stressed the need to look
at such evidence critically because its writers could not be
cross-examined themselves. Such scientific evidence only becomes a
factor for consideration if it is "intelligible, convincing and
tested". (109) Accordingly, in Scotland, the cases are at one in
emphasizing that where a pursuer seeks to rely on epidemiological
evidence of disease to prove causation, the pursuer must impart to the
court special knowledge of the subject matter of epidemiology, so that
the court can form its reasoned judgment on the epidemiological
evidence. (110)

Such a cautious approach to epidemiological evidence was central to
the decision in McNair. While sympathetic to the experts who were
"out with their chosen disciphne and abroad in the field of
epidemiology," (111) Lord McEwan concluded nonetheless that the
experts were unable to explain the studies, which seemed to him to
"raise more questions than answers." (112) Unlike McTear,
however, McNair shows less of an impression of what Chris Miller has
described as a "dogmatic aversion" (113) to statistical
evidence. Lord McEwan felt that many of the concerns about the evidence
might have been assuaged if the authors of the reports had been called
to testify and if there had been some statistical evidence presented.
Without such assistance, the judge was "at once disabled from being
able properly to evaluate the worth of the study or to draw the proper
conclusions." (114) In his view, therefore, this was an appropriate
case for epidemiologists to give evidence and for experts to explain
their studies. He did not, however, believe that this was always the
case, and he suggested that reliance on doctors and epidemiologists
"can almost lead the court unwittingly into a kind of satellite
litigation on issues away from the pursuer's case." (115) He
seemed to regard McTear and another Scottish decision, Dingley, (116) as
two recent examples of this. (117) However, the use of statistics in
determining causation is hardly satellite litigation. In both McTear and
Dingley, it was a primary issue which required resolution in the face of
scientific uncertainty. The concern with Scots law taking such a
cautious approach to epidemiological evidence is therefore that such an
approach may make it harder to even discern that there is any possible
reconciliation of the legal standard of proof on a balance of
probabilities with the scientific standard of statistical significance.

Even more importantly, there is also concern that the placing an
obligation on a plaintiff to teach epidemiology to a court suggests that
the court can remain passive in this process. This is surely an
unhelpful approach in cases such as McTear and in cases involving
adverse reactions allegedly caused by medicinal products. In such cases,
there is a clear social expectation that judges will resolve these
matters to the satisfaction of both parties. As a leading American judge
has observed about cases where judges preside over non-jury trials:

Passivity of the court is no virtue when serious scientific
questions of more than passing importance are involved. The court
owes an obligation to the parties, to society, and to itself to
assist in obtaining the best possible answers to the scientific
questions before it. That will mean forcing the parties to gather
and present evidence effectively, calling upon other experts as
necessary, and studying to obtain the understanding needed to
maintain effective control. (118)

Had the pursuer in McTear explained the epidemiological evidence
properly, and had Lord Nimmo Smith been more receptive to evidence of
relative risk as well as taken a more active role in forcing the pursuer
to present her evidence effectively, it would seem that general
causation could have been established. Moreover, Lord Nimmo Smith should
have given more weight (119) to the surely important fact that the
defenders admitted that the World Health Organization, along with the
governments of the United Kingdom and the United States, had accepted
for many years that cigarette smoking can cause lung cancer. (120)

Of course, irrespective of the conclusions on general causation,
there remained the problem of establishing individual causation in the
context of "naked statistical evidence". (121) It is to this
that we now turn.

E. The Statistical Chance/Personal Chance Dichotomy

It has been argued that there is a dichotomy between two kinds of
chances--one "statistical" and the other "personal".
A statistical chance is a figure collected from "previous
unconnected outcomes, giving a probability of that outcome in any
non-individual case," whereas a personal chance is "peculiar
to a particular individual." (122) A statistical chance has no
compensatory value, until the data is "personalised". (123)

The impossibility of applying statistics derived from
epidemiological studies to determine causation in individual cases was
cited as the principal reason for the pursuer's failure to prove
individual, or specific, causation in McTear. Epidemiological evidence
could not prove that it was more likely than not that but for his
smoking of cigarettes, the deceased would not have contacted lung
cancer. (124) As Lord Nimmo Smith put it:

The information provided in an observational epidemiology is
generally such that it can neither confirm nor refute a causal
relationship, particularly when the exposure in question is not
specifically associated with a certain condition (ie the exposure
is always associated with the condition, and vice versa).
Epidemiology cannot provide information on the likelihood that an
exposure produced an individual's condition. The population
attributable risk is a measure for populations only and does not
imply a likelihood of disease occurrence within an individual,
contingent upon that individual's exposure. The fact that cases and
non-cases can emerge both from the unexposed and the exposed groups
show that the likelihood of the individual occurrence cannot be
reliably predicted from his or her exposure group membership alone.
The group estimates obscure the underlying heterogeneity of the
population, so that it is entirely possible that other group
memberships besides exposure, like genetic profile, socio-economic
status, workplace, diet and other exposures make a major
contribution to disease occurrence. The question of using
epidemiological data for individual causation raises the problem of
identifying a particular individual who was harmed by the exposure.
While models such as the assigned share concept, derived from
attributable fractions, have attempted to deal with this, they
suffer from the limitations mentioned by Dr Lewis. The attempt to
identify exposure as the sole cause of disease in an individual
produces a statement counter to fact in that it implies that the
individual would have remained healthy if the exposure had not
occurred. This, as Dr Lewis said, is not provable and cannot be
derived from epidemiological data. (125)

Lord Nimmo Smith concluded that, given there were other possible
causes of lung cancer other than cigarette smoking, and given that lung
cancer could occur in a non-smoker, it was not possible to determine in
any individual case whether but for an individual's cigarette
smoking he probably would not have contracted lung cancer. (126) In
doing so, Lord Nimmo Smith referred to "[t]he fallacy of applying
statistical probability to individual causation." (127)

However, his dicta require closer scrutiny. While Lord Nimmo Smith
was correct to observe that there are limitations to epidemiological
evidence, his description of these limitations is somewhat inaccurate.
In stating that "group estimates obscure the underlying
heterogeneity of the population, so that it is entirely possible that
other group memberships besides exposure, like genetic profile,
socio-economic status, workplace, diet and other exposures make a major
contribution to disease occurrence," (128) he fails to appreciate
that epidemiologists can and do adjust for these potentially confounding
factors through logistic regression statistical techniques. (129)
Notwithstanding Lord Nimmo Smith's doubts about causal proof based
on population estimates of relative risk, these estimates are relevant
to individual cases, even though they do not directly measure the
probability of causation in an individual case. (130) Moreover, Miller
has suggested that, while Lord Nimmo Smith's "dogmatic
aversion to statistical evidence" means that epidemiology alone
will never secure recovery in respect of specific causation in such
cases, (131) use of epidemiological evidence that satisfies the criteria
developed by Sir Austin Bradford Hill would seem to be hard to gainsay.
(132) Thus, Miller has argued that if an individual had been one of the
cases in a case control study that yields strength of association
(relative risk), then in light of such strength of association and other
Bradford Hill criteria, "it seems perverse to hold that it is less
probable than not that the exposure caused that individual's
condition." (133) I contend that Miller is correct in concluding
that a causal relationship would exist in such circumstances. Indeed,
Sir Austin Bradford Hill emphasized that "[n]one of my nine
viewpoints can bring indisputable evidence for or against the
cause-and-effect hypothesis and none can be required as a sine qua
non," (134) and this has been judicially approved in the United
States. (135) Sir Austin Bradford Hill specifically cautioned against
overly emphasizing the importance of specificity at the expense of
strength of association, referring specifically to smoking and lung
cancer. (136) In doing so, he provided a particularly apt example:

Coming to modern times the prospective investigations of smoking
and cancer of the lung have been criticized for not showing
specificity--in other words the death rate of smokers is higher than
the death rate of non-smokers from many causes of death. ... But
here surely one must return to my first characteristic, the
strength of association. If other causes of death are raised 10, 20
or even 50% in smokers whereas cancer of the lung is raised
900-1,000% we have specificity--a specificity in the magnitude of
the association.
...
We must also keep in mind that diseases may have more than one
cause.
...
In short, if specificity exists we may be able to draw conclusions
without hesitation; if it is not apparent, we are not thereby
necessarily left sitting irresolutely on the fence. (137)

I suggest that Lord Nimmo Smith in McTear undervalued the
significance of the widely accepted magnitude of strength of association
between cigarette smoking and cancer, and that he was wrong to treat the
Bradford Hill factors as criteria that all needed to be satisfied before
such an association could amount to a causal connection between smoking
and lung cancer. In his discussion of the impossibility of applying
statistics derived from epidemiological studies to determine causation
in individual cases, Lord Nimmo Smith failed to appreciate that, in
determining specific causation, epidemiologists can and do adjust for
potentially confounding factors through logistic regression techniques
and other forms of statistical refining mechanisms. It is to these
techniques that we now turn.

The problem of using statistics deriving from trends in general
populations to prove causation in an individual case has been recognized
judicially by the House of Lords in Hotson v. East Berkshire Area Health
Authority (138) and in Gregg v. Scott, (139) and by the UK Supreme Court
in Sienkiewicz v. Greif. (140)

Yet it is arguable that while epidemiological evidence reaches
conclusions on the incidence of a disease in a population in the form of
relative risk, this relative risk can be refined to draw conclusions
about the cause of disease in an individual using specific risk factors,
(141) such as those present in Mr. McTear's case and in Mr.
Peterson's case. This has been accepted by American courts in the
context of pharmaceutical product liability litigation. (142) In McDarby
v. Merck & Co, Inc., (143) a case involving the drug Vioxx,
epidemiological evidence was combined by experts with the presence of
the plaintiffs personal heart attack risk factors, namely his age, low
levels of "good" cholesterol, weight, and diabetes. The New
Jersey court regarded this as ample evidence to support an increased
risk resulting from the combined effects of diabetes and Vioxx, and
concluded that Vioxx had been a substantial contributing factor to the
plaintiff's heart at tack. (144) In so concluding, the court
applied a substantial factor standard in the context of concurrent
causation, in preference to the 'Taut for" test. (145)

In this context, I have suggested that statistics regarding
evidence of general causal links between a drug and an injury (a
statistical chance) could be refined into statistics establishing a
specific causal link between the drug and the adverse reaction in the
case at issue (a personal chance) (146) using logistic regression
techniques and other forms of statistical refining mechanisms. (147)

Logistic regression techniques identify determinants of a
particular outcome and assess the extent of the contribution of these
determinants, adjusting for confounding factors (148) that may influence
the contribution. (149) Logistic regression is also closely linked to
other forms of statistical refining, such as Bayes' theorem.
Bayes' theorem can modify evaluations of probability based on
initial assumptions in the light of more data that later becomes
available. It expresses the relationship between the probability of a
proposition (A) evaluated before the utilization of new data (B) (prior
probability), and the probability of the same proposition evaluated
after the utilization of the new data (posterior probability).

Thus:

Posterior Prior Probability of A Probability of B given A
Probability
of A given B = 1 x Unconditional Probability
of B

i.e. P(A/B) = P(A) x [P(B/A)/ P(B)]

Prior probabilities can therefore be updated in the light of new
data from epidemiological studies as they accumulate, providing both
fact finders in individual product liability cases, and policy-makers
such as the Food and Drug Administration and the European Medicines
Agency, with an update of the estimated risk. (150) The main difficulty
with such posterior probabilities is that frequentist statisticians
(151) who rely on epidemiological evidence regard them as necessarily
subjective, since they reflect not only data but also subjective prior
probabilities. (152) However, "objective Bayesians" (153) use
Bayes' theorem without eliciting prior probabilities from
subjective beliefs, avoiding the charge of subjectivism. (154) This has
been supported in the pharmaceutical product liability context by
Professor Joseph Gastwirth, who has adopted a data-based approach to
ensure that the choice of prior distribution is objective and unbiased.
He uses the first case control study or an analysis of adverse event and
case reports to determine two prior distributions, one the most
favourable to the defendant, and the other centred on or near the
estimated relative risk from the first study. This method of determining
two prior distributions restricts the degree of subjectivity that an
analyst can insert into a Bayesian approach. This is very important in
the legal context, where lawyers would likely choose the expert who
obtains the more favourable result for them. The data-based approach
helps to avoid bias in the choice of prior distribution. (155) Others
have also tried to apply Bayes' theorem in the evaluation of the
reliability of medical and scientific evidence in toxic tort cases.
(156) However, the strongest criticism of Bayes' theorem is the
difficulty of arriving at a sufficiently accurate evaluation of a
pre-existing probability to which experimental data can be applied.
(157)

Bayes' theorem tells us that the value of a piece of evidence
in testing a particular assertion is determined by its likelihood ratio.
The likelihood ratio (LR) is the probability of the evidence supposing
our assertion is true, divided by the probability of the evidence if the
assertion is not true. (158) The Centre for Evidence Based Medicine at
the University of Oxford provides a helpful example of the LR in the
following:

[Y]ou have a patient with anaemia and a serum ferritin of 60mmol/l
and you find in an article that 90 per cent of patients with iron
deficiency anaemia have serum ferritins in the same range as your
patient (= sensitivity) and that 15 per cent of patients with other
causes for anaemia have serum ferritins in the same range as your
patient (1 - specificity). This means that your patient's result
would be six times as likely (90/15) to be seen in someone with, as
opposed to someone without, iron deficiency anaemia, and this is
called the LR for a positive test result. (159)

An alternative statement of Bayes' theorem explains it in
terms of odds. (160) Bayes' theorem expresses the relationship
between the odds in favour of a hypothesis before the utilization of new
data (prior odds) and the odds in favour of the hypothesis after taking
into account the new data (posterior odds). The prior odds must be
multiplied by the likelihood ratio of the new piece of data to generate
the posterior odds.

Thus:

Posterior Odds = Prior Odds x Likelihood Ratio

Applying this to the Peterson case, (161) "Vioxx-induced
MI" could be compared with a catch-all alternative, "no
Vioxx-induced MI". Alternatively, one could compare
"Vioxx-induced MI" with some specific alternative, such as
"diet-induced MI", "totally uncaused MI", or
"no MI". The likelihood ratio would then be the ratio of the
probabilities of developing MI under these two hypotheses. (162)

A statistical chance could be refined and personalized into a
personal chance using specific factors which are embodied in the
likelihood ratio. The probabilities in the likelihood ratio can be
decomposed into factors in the light of specific case information in
respect of patient history. Such factors could include the risk factors
in Peterson, (163) namely Peterson's age (LR (Ag)), gender
hypertension (LR (Gh)), hyperlipidaemia (LR (Hypl), obesity (LR (Ob)),
left ventricular hypertrophy (LR (LVH)), and a history of smoking (LR
(Hs)). (164) The likelihood ratio is then found by obtaining the product
of all the individual likelihood ratio factors.

The use of all these factors is dependent on the specific case
information available. If all specific case information in respect of
the factors is available, the posterior odds are calculated as follows:

Thus the posterior odds can be further refined by combining the
prior odds, based on background information, with the likelihood ratios,
based on case-specific information, to produce as accurate a posterior
probability as possible. (165) The nature of each risk factor likelihood
ratio can represent a particularistic property of the individual
claimant, provided they can be determined in the case in issue. (166)
There is therefore a need to obtain statistics with an evidentiary
foundation before such likelihood ratios can be calculated. (167)

This would seem to be a possible tool that can improve
probabilistic precision in the Peterson-type case and in other cases
involving medicinal products. In so doing, this tool can overcome the
difficulties associated with the statistical chance/personal chance
dichotomy.

It is clear that while Bayes' theorem could provide a
normative approach to legal decision making in the context of causation
and medicinal products, implementing the theorem, in practice, is likely
to be difficult. (168) We have seen that Bayes' theorem assumes the
presence of conditionally independent new evidence to update the
previous evidence, but this new evidence is absent in many cases
involving alleged adverse drug reactions. This complicates the
application of the theorem. The use of individual risk factor likelihood
ratios in respect of individual items of evidence is potentially
valuable, but these may be difficult to calculate in practice. It should
also be conceded that if sample sizes are so small that one cannot
disaggregate data to provide information on individual risk factors,
then the statistical refining process will fail. Moreover, while more
detailed individual ratios might improve the accuracy of the posterior
odds, the introduction of too many additional quantities with imperfect
estimation could degrade it. (169) However, the basic point here is not
to suggest that Bayes' theorem is necessarily the answer to the
problem of establishing specific causation in the context of
epidemiological evidence. It is rather that logistic regression
techniques and other forms of statistical refining mechanisms using
specific risk factors can and do help in the process of giving
quantitative or quasi-quantitative expression to conclusions about the
cause of disease in an individual claim that is based on epidemiological
evidence.

Support for the refining and personalizing of epidemiological
evidence in cases of individual causation involving medicinal products
is now gaining traction in courts. One relevant recent case is Andersen
v. St Jude, a Canadian trial on the merits of a class claim concerning
the "safety of the mechanical prosthetic heart valves and
annuloplasty rings with Silzone that were designed and manufactured by
the defendants and approved for sale in Canada in the late 1990s."
(170) In Andersen, the Ontario Superior Court recognized that the
doubling of risk standard is merely a presumptive threshold, so that a
negative finding on causation could be rebutted using probative
individualized evidence in a subsequent individual trial. (171)

Silzone was a proprietary term for a coating comprising layers of
titanium, pallodium, and an outer layer of metallic silver, which was
applied to a polyester sewing cuff that surgeons used to attach a
prosthetic heart valve to heart tissue. Silver is known as an
antimicrobial, and the Silzone coating was designed to inhibit the
growth of bacteria that could cause endocarditis, an infection of the
lining of the heart that is a potential serious complication of heart
valve surgery. Other than the application of the coating to the sewing
cuff, "the Silzone valves were of the same design as conventional
mechanical valves that the defendants had manufactured for many
years." (172) Following a randomized clinical trial called AVERT,
which had "revealed a small, but statistically significant increase
in expiants due to a medical complication known as paravalvular leak
(PVL) in patients who had received a Silzone implant," the
defendants in Andersen issued a worldwide recall of all Silzone-coated
products in early 2000. (173) A class action against St. Jude Medical
was commenced in 2001. At its core was a claim in negligence, which
focused on the breach of St. Jude's duty of care to patient class
members and questions of general causation. (174)

The plaintiffs advanced the theory that Silzone [was] a toxic
substance that interfere[d] with the cells involved in tissue
healing and impaired] the body's ability to properly incorporate
the Silzone device into the heart, thereby causing or contributing
to a variety of serious medical complications for Silzone patients.
As medical complications can occur with all prosthetic heart
valves, a key inquiry in this trial was whether Silzone ...
materially increased [the] risk of [patients] experiencing one or
more of these complications. (175)

While the couching of this inquiry in terms of "material
increase in risk" may seem peculiar, (176) the issue being
addressed was whether the plaintiffs could prove that the Silzone valve
caused a true excess risk of the medical complications--above the risk
caused by the conventional valves. In essence, the Ontario Superior
Court was adopting the same approach to the issue as the English High
Court in XYZ v. Schering Health Care Ltd. (177)

Notwithstanding that Justice Lax found that the defendants did not
breach any duty of care in the pre-market design, manufacture, and
testing, or in the post-market surveillance, warning, and recall of
Silzone-coated products, (178) she proceeded to determine the common
issues of causation had the court found differently on the breach of
duty issue. She explained that

statistical epidemiological evidence ha[d] been presented to aid
[her] in determining whether or not Silzone valve patients
experience a higher risk of medical complications than conventional
valve patients. In other words, the purpose of this evidence [was]
to determine the risk of medical complications posed by the Silzone
valve relative to the risk posed by the conventional valve. (179)

This introduced the concept of relative risk, which was "a
numerical expression of the risk of medical complications for one class
of patients relative to another." (180) While recognizing the
limitations of epidemiological evidence, in that it ought not to be
considered determinative of individual causation, (181) Justice Lax used
simple arithmetic, the application of the 'hut for" test, and
the balance of probabilities standard to conclude that for the purposes
of issues of general causation in a class action trial, a doubling of
risk standard should be adopted. A product (here the Silzone valve)
thereby creates a material risk of an adverse event where the risk is at
least twice the risk of the adverse effect occurring in the absence of
the product's use (namely, when using the conventional valve).
(182)

However, in an important development which may help to constrain
the emergence of overly optimistic emphasis on doubling of risk as some
magic formula with which to prevent cases from going forward to trial in
the future, Justice Lax explained that the establishment of material
risk and the application of the doubling of risk standard were not
determinative of individual causation. Instead, for the purpose of
individual class member claims, the application of the doubling of risk
standard is merely a presumptive as opposed to a prescriptive threshold,
so that a negative finding on causation (where the relative risk is
below two) could be rebutted using probative individualized evidence in
a subsequent individual trial. (183) Justice Lax added that if she had
found the defendants to be negligent, she would have presumptively
applied the doubling of risk standard for materiality. (184)
Accordingly, patients who suffered complications for which the increase
in risk was not material (i.e., where the relative risk was below two)
or even not statistically significant would still be able to recover at
the individual stage of those proceedings, provided they presented
sufficient individualized evidence to rebut the presumption of a lack of
causation flowing from a relative risk below two, and that they were
able to persuade their trier of fact that Silzone was the "but
for" cause of their complications. (185) The benefit of adopting
this approach is that "it does not shut the door on individual
class members solely on the basis of evidence regarding group
risk." (186) As Justice Lax explained, the adoption of a
presumptive approach to materiality, permitting negative findings on
causation to be rebutted by individualized evidence, allowed her to
advance the litigation and to outline how a trier of fact at the
individual stage of similar proceedings could properly utilize relative
risk as ascertained by epidemiological data. (187)

Conclusion

We can make the following observations about recent cases from the
United Kingdom that examine the role of epidemiological evidence in
assessing causation in medicinal product liability claims.

There remain considerable difficulties in reconciling standards of
proof in law and in science. Despite the trenchant criticisms of the
doubling of risk theory in the United States, the theory appears to be
gaining ground in the United Kingdom. However, the majority of the UK
Supreme Court in Sienkiewicz appears to be sceptical of introducing a
threshold for the use of epidemiological evidence and remain of the view
that such evidence can be useful but must be viewed with caution.
Without further nonstatisticail evidence, there is reluctance for courts
to proceed to find the existence of a causal relationship. The danger
otherwise is that counsel, in assessing the chances of success of
"no win, no fee" multi-party product liability litigation,
especially that which involves medicinal products, may regard this
doubling of risk theory as the sole basis on which to allow or prevent
cases from going forward to trial, even where epidemiological evidence
is lacking. This could potentially prejudice access to justice in future
cases. If the doubling of risk approach is to be embraced by UK courts,
it should be treated as it was in the Canadian decision of Andersen,
where the standard operated as merely a presumptive as opposed to a
prescriptive threshold, so that a negative finding on causation (where
the relative risk is below two) could be rebutted using probative
individualized evidence in a subsequent individual trial. In such cases
where there is a dearth of epidemiological evidence, courts and, for
that matter, funding bodies should learn from the US experience and
should avoid insisting on epidemiological studies which have a relative
risk of greater than two, allowing all evidence which falls "within
a zone of reasonable [scientific] disagreement" (188) to be
considered.

While it seems the United Kingdom is becoming more receptive to the
need for epidemiologists to come to court to speak to their evidence and
for it to be taught to the fact finder, courts have nonetheless recently
developed an overly cautious approach to the use of epidemiological
evidence, particularly in Scots law. We have seen two main reasons for
judicial scepticism about epidemiological evidence emerging from the
case law, namely the propriety of drawing causal inferences from
observed associations (a general causation issue) and the propriety of
drawing causal inferences in individual cases from concededly causal
associations observed in samples of populations (a specific causation
issue). The concern with taking such a cautious approach to
epidemiological evidence is that it may make it harder to discern that
there is any reconciliation of the legal standard of proof on a balance
of probabilities with the scientific standard of statistical
significance. Moreover, there is also concern that placing an obligation
on a plaintiff to teach epidemiological analysis to a court suggests
that the court can remain passive in this process. This is surely an
unhelpful approach in cases such as McTear, where there is a clear
societal expectation that a judge will resolve these matters to the
satisfaction of both parties. Had the pursuer explained the
epidemiological evidence properly, and had Lord Nimmo Smith been more
receptive to evidence of relative risk, taken a more active role in
forcing the pursuer to present her evidence effectively, and given
adequate weight to the generally accepted scientific evidence that
cigarette smoking can cause lung cancer, general causation could have
been established in this case.

There also remains a lack of clarity on the extent to which
generalized epidemiological evidence can be useful in determining
individual, or specific, causation. Accordingly, this paper supports the
use of logistic regression techniques and other forms of statistical
refining mechanisms using specific risk factors to give quantitative or
quasi-quantitative expression to conclusions about the cause of disease
in an individual drug product liability claim that is based on
epidemiological evidence. Logistic regression is also closely linked to
other forms of statistical refining such as Bayes' theorem. We have
seen that while Bayes' theorem can modify evaluations of
probability based on initial assumptions in light of more data using
specific factors embodied in the likelihood ratio, implementation of the
theorem, in practice, is likely to be difficult. It is important to
stress that Bayes' theorem is not necessarily the answer to the
problem of establishing specific causation in the context of
epidemiological evidence. However/ the crucial point is that statistical
refining mechanisms using specific risk factors can assist courts in
determining specific causation in drug product liability cases when the
dominating evidence is epidemiological in nature. This is likely to be
increasingly true, as the quality of scientific evidence increases with
time. (189)

It has been suggested that this approach could have been adopted
with the specific case information available in Peterson, instead of the
plaintiffs personal circumstances being blindly treated as diminishing
the strength of the epidemiological evidence. (190) Indeed, the
interdisciplinary Vaccine Safety Committee of the Institute of Medicine
adopted such an "informal Bayesian approach" to assessing case
reports in its review of scientific and medical literature on specific
risks to children associated with vaccines. (191) Courts could use this
information to refine generalized statistics to produce as accurate a
posterior probability as possible, especially in the pharmaceutical
field. This, however, would require epidemiologists and physicians to
assist courts in such an exercise, and clearly, without courts having
access to existing prior probabilities and the ability to quantify
likelihood ratios, the utility of the process would be limited. (192)

Notwithstanding the scepticism of the majority of the UK Supreme
Court in Sienkiewicz, there is little doubt that the use of
epidemiological evidence in medicinal product liability cases,
especially where nonnumerical solutions are elusive, has now come of
age. Albeit with caution, courts are recognizing the importance of such
evidence. The challenge is now for lawyers and epidemiologists to come
to some consensus as to what amounts to a suitable use of
epidemiological evidence in such cases when establishing proof on a
balance of probabilities. It is arguable that the so-called doubling of
risk approach mooted in Sienkiewicz is overly simplistic. In particular,
doubling of risk does not consider absolute risk (that is, the risk of
something occurring without any context) (193) and the severity of the
outcome. Any attempt to reach a consensus in the future must address
these, and related, difficult issues.

(2) Richard Goldberg, Causation and Risk in the Law of Torts:
Scientific Evidence and Medicinal Product Liability (Oxford: Hart
Publishing, 1999) 5 et seq [Goldberg, Causation and Risk in the Law of
Torts\.

(3) Harvey Teff and Colin Munro, Thalidomide: The Legal Aftermath
(Farnborough: Saxon House, 1976) at 135-36. "Clearly it is often
harder to prove that one's injuries are due to an adverse drug
reaction than that they have been caused by a faulty machine"
(Harvey Teff, "Regulation Under the Medicines Act 1968: A
Continuing Prescription for Health" (1984) 47:3 Mod L Rev 303 at
322). Professor Teff also notes "[t]he synergistic effects of
certain combinations (for example, barbiturates and alcohol,
anti-histamines and cheese) may prove fatal" (Harvey Teff,
"Products Liability in the Pharmaceutical Industry at Common
Law" (1974) 20:1 McGill LJ 102 at 115).

(4) See e.g. Bonthrone v Secretary of State for Scotland, 1987 SLT
34, Jauncey LJ, cited in Diana Brahams, "Pertussis Vaccine and
Brain Damage: Two Claims Before the Courts" (1985) 326 Lancet 1137
(on the existence of cryptogenic (unknown) causes to eliminate any
possible causal connection between the pertussis vaccine and brain
damage); see also Loveday v Renton (1988), [1990] 1 Med LR 117 (QB) at
185 [Loveday], Stuart-Smith LJ, discussed in Goldberg, Causation and
Risk in the Law of Torts, supra note 2 at 137-43 (after examining
complex scientific evidence and arguments, Lord Stuart-Smith held that
the plaintiff had failed to prove on a balance of probabilities that the
pertussis (whooping cough) vaccine could cause permanent brain damage in
young children); Kay v Ayrshire and Arran Health Board, [1987] 2 AU ER
417, 1987 SC 145 (HL Eng) (penicillin overdose was held to be not
capable of causing or aggravating deafness). Consider also the US mass
tort litigation concerning Bendectin (Debendox), the anti-nausea drug
used in pregnancy. In contrast to thalidomide, where many lines of
evidence have shown that the drug caused phocomelia malformations (see
Henning Sjostrom & Robert Nilsson, Thalidomide and the Power of the
Drug Companies (Harmondsworth: Penguin, 1972) at 156-59), no causal link
has ever been scientifically established between Bendectin and birth
defects. The Bendectin litigation demonstrated a persistent failure by
plaintiffs' lawyers to prove causation. Joseph Sanders wrote the
seminal paper on this topic: "The Bendectin Litigation: A Case
Study in the Life Cycle of Mass Torts" (1992) 43:2 Hastings LJ 301.
For a discussion of the litigation's implications in the United
Kingdom, see Goldberg, Causation and Risk in the Law of Tort, supra note
2 at 102-31. The litigation spawned two formative monographs: Michael D
Green, Bendectin and Birth Defects: The Challenges of Mass Toxic
Substances Litigation (Philadelphia: University of Pennsylvania Press,
1996); Joseph Sanders, Bendectin on Trial: A Study of Mass Tort
Litigation (Ann Arbor: University of Michigan Press, 1998). Thirty years
after Bendectin's withdrawal from the market, the drug (now renamed
Diclegis) has won Food and Drug Administration approval as the only
FDA-approved treatment for morning sickness (FDA News Release, "FDA
approves Diclegis for pregnant women experiencing nausea and
vomiting", online: US Food and Drug Administration
<www.fda.gov/NewsEvents/
Newsroom/PressAnnouncements/ucm347087.htm>, accessed 13 April 2013;
Associated Press, "Morning Sickness Drug Returns", The New
York Times (8 April 2013), online: The New York Times
<www.nytimes.com/2013/04/09/us/moming-sickness-drug-retums.html?
emc=tnt&tntemail1=y&_r=0&pagewanted=print>).

(5) EC, Council Directive 85/374/EEC of 25 July 1985 on the
Approximation of the Laws, Regulations and Administrative Provisions of
the Member States Concerning Liability for Defective Products, [1985]
OJ, L 210/29. By article 4 of the Directive, and section 2(1) of the
Consumer Protection Act 1987 (UK), c 43, s 2(1), the person injured by a
defective medicinal product must prove the damage, the defect, and the
causal relationship between them. The damage must have been caused
"wholly or partly by a defect" in the medicinal product. Thus
the formal distinction between negligence and strict liability is that
with negligence, it must be proven that breach of a duty caused the
harm, whereas under the 1987 Act, it must be proven that a defect caused
the damage (see Pamela R Ferguson, Drug Injuries and the Pursuit of
Compensation (London: Sweet & Maxwell, 1996) at 125). It appears
that each member state will rely on its own theory of causation as
established in its civil liability system, though it has been observed
that some kind of semi-autonomous European understanding of causation
could be established from common elements of the member states'
legal systems (see Simon Whittaker, "The EEC Directive on Product
Liability" (1985) 5 YB Eur L 233 at 247). The argument that
causation is likely to be defined and interpreted by national law and
assessed by national courts is strengthened by the decision of the
European Court of Justice in Henning Veedfald v. Arhus Amtskommune,
where the Court concluded that it was for the national court to decide
whether a claim was to be categorized in respect of personal injury,
property damage, or non-material damage (C-203/99 [2001] ECR 1-3587 at
I-35993600). This is subject to a qualification founded on the principle
of effectiveness, in that national laws must not by their interpretation
of causation render ineffective either the protection of injured persons
or the restraints on liability of producers, since both reflect the
"fair apportionment of risk" of the Directive. In so doing,
however, courts will take into consideration the extent to which these
causal issues combine issues of fact and their evaluation and questions
of law (see Simon Whittaker, Liability for Products: English Law, French
Law, and European Harmonisation (Oxford: Oxford University Press, 2005)
at 512-13). The European Commission believes that "injured parties
can establish the causal link in cases where a defective product causes
damage irrespective of the differences between national procedural
rules" (EC, Fourth Report on the Application of Council Directive
85/374/EEC of 25 July 1985 on the Approximation of the Laws, Regulations
and Administrative Provisions of the Member States Concerning Liability
for Defective Products (Brussels: EC, 2011) at 11), though it has noted
the views of consumers that there is difficulty in "proving the
causal link between the defect and damage when such damage is complex in
nature" (ibid at 7). Consumers believe that the burden of proof
should be reversed (ibid).

(19) See Green, "Epidemiology", supra note 8 at 577 n 81.
Equating statistical significance with the legal burden of proof has
been described as being "like trying to find the shortest path from
Oxford to Cambridge by scrutinizing a map of London" (DH Kaye,
"Apples and Oranges: Confidence Coefficients and the Burden of
Persuasion" (1987) 73:1 Cornell L Rev 54 at 66). Kaye demonstrates
the distinction between statistical significance and the civil burden of
persuasion by using a hypothetical case (ibid at 66-73). There is often
judicial reference to a statement that the level of 0.05 for statistical
significance is a much higher burden of proof than the civil burden of a
preponderance of the evidence or balance of probabilities (that is,
greater than fifty per cent): see Green, "Epidemiology", supra
note 8 at 577, citing In re Ephedra Products Liability Litigation, 393 F
Supp (2d) 181 at 193 (SD NY 2005); Marmo v IBP, Inc, 360 F Supp (2d)
1019 at 1021 (D Neb 2005); Peter Feldschreiber, Leigh-Ann Mulcahy &
Simon Day, "Biostatistics and Causation in Medicinal Product
Liability Suits" in Richard Goldberg, ed, Perspectives on Causation
(Oxford: Hart, 2011) 179 at 190. Recent case law has referred to
Wyeth's citation of the Reference Manual on Scientific Evidence to
point to the erroneous nature of this approach (see Giles v Wyeth, Inc,
500 F Supp (2d) 1048 at 1056-57 (SD Ill 2007)).

(24) See Carter, supra note 22 at para 97. A confidence interval or
confidence limit is a range of values within which the true value is
likely to fall (see Green, "Epidemiology" supra note 8 at 621;
Goldberg, Causation and Risk in the Law of Torts, supra note 2 at 137;
American Law Institute, Reporters' Study: Enterprise Responsibility
for Personal Injury, vol 2: Approaches to Legal and Institutional Change
(Philadelphia: American Law Institute, 1991) at 324-28).

(25) Vadera v Shaw (1998), 45 BMLR 162 (CA), (2000) 8 Med LR 316.

(26) Ibid at 174. However, it is suggested that there was a failure
by the trial judge and the Court of Appeal to scrutinize adequately the
scientific evidence in respect of causation in this case (see Richard
Goldberg, "The Contraceptive Pill, Negligence and Causation: Views
on Vadera v. Shaw" (2000) 8 Med L Rev 316 at 331-35).

(29) See especially Daubert u Merrell Dow Pharmaceuticals, 43 F
(3d) 1311 (9th Cir 1995), 63 USLW 2420, cert denied, 516 US 869, 116 S
Ct 189 (1995) [Daubert II]. In that case, the Court of Appeals, on
remand from the Supreme Court of the United States, held that the
plaintiffs had to show not merely that Bendectin increased the
likelihood of injury, but that it more likely than not caused their
injuries. In terms of statistical proof, it had to be shown that
plaintiffs' mothers' ingestion of Bendectin more than doubled
the likelihood of birth defects (ibid at 1320). This was reaffirmed by
the Supreme Court of Texas in Havner, supra note 10 at 716-18. The
Supreme Court of Texas has now expanded on its holding in Havner and
adopted the position that a doubling of risk is a necessary but not
sufficient condition to prove causation (see Garza, supra note 10 at
265). Vermont has also adopted the doubling of risk theory in a slightly
diluted form in the context of specific causation (see Blanchard v
Goodyear Tire and Rubber, 30 A (3d) 1271, 2011 VT 85 (Vt Sup Ct) at
1275-77). For an excellent discussion of the implications of both cases,
see Steve C Gold, "Revisiting Relative Risk Rules: Garza,
Blanchard, and the Ever Evolving Role of Epidemiologic Proof in Toxic
Tort Cases" (2012) 40 Prod Safety & Liab Rep (BNA) 50 [Gold,
"Revisiting Relative Risk Rules"].

(31) See e.g. Lucinda M Finley, "Guarding the Gate to the
Courthouse: How Trial Judges Are Using Their Evidentiary Screening Role
to Remake Tort Causation Rules" (1999) 49:2 DePaul L Rev 335
(criticizing the doubling--in-risk evidentiary requirement for
epidemiological proof, describing the trend as "seriously
scientifically and legally misguided" at 348); Margaret A Berger,
"Upsetting the Balance Between Adverse Interests: The Impact of the
Supreme Court's Trilogy on Expert Testimony in Toxic Tort
Litigation" (2001) 64:2-3 Law & Contemp Probs 289 (criticizing
the doubling of the risk rule as "a legal invention that creates a
hard and fast rule that disposes of cases efficiently but rests on
assumptions that cannot be scientifically validated at this time"
at 304-06); Sander Greenland & James M Robins, "Epidemiology,
Justice, and the Probability of Causation" (2000) 40:3 Jurimetrics
J 321 at 325-26; Mark Geistfeld, "Scientific Uncertainty and
Causation in Tort Law'" (2001) 54:3 Vand L Rev 1011 at
1015,1018, 1020.

(32) Finley, supra note 31 at 336.

(33) Ibid; see also Jean Macchiaroli Eggen, "Clinical Medical
Evidence of Causation in Toxic Tort Cases: Into the Crucible of
Daubert" (2001) 38:2 Hous L Rev 369 at 378-79; Michael D Green,
"The Future of Proportional Liability: The Lessons of Toxic
Substances Causation" in M Stuart Madden, ed, Exploring Tort Law
(Cambridge: Cambridge University Press, 2005) 352 at 368-69. A recent
instance of the conflation of both admissibility and sufficiency of
evidence requirements is Garza, supra note 10, discussed in Gold,
"Revisiting Relative Risk Rules", supra note 29 at 53 (where
he argues that by framing a totality of evidence test as a matter of
reliability, Garza explicitly conflated rules of admissibility and
substantive sufficiency in the weighing of evidence).

(41) See Cookson v Novartis Grimsby Ltd, [2007] EWCA Civ 1261,
[2007] All ER (D) 465 (Nov) at para 74, Smith LJ. See also Ministry of
Defence v AB, [2010] EWCA Civ 1317, 117 BMLR 101 at 149 [AB]. In the
appeal for AB (AB v Ministry of Defence, [2012] UKSC 9, [2013] 1 AC 78
[AB UKSC]), the UK Supreme Court found the doubling of risk theory
relevant in the context of examining the strength of claimants'
cases on causation and in determining whether the trial court's
exercise of discretion under section 33 of the Limitation Act 1980 was
appropriate. The trial judge was found to have wrongly exercised his
discretion. In dismissing the claimants' appeals, the Supreme Court
observed that it was undesirable that a court which conducts an inquiry
into whether a claim is time-barred should, even when it considers its
power under section 33 of the 1980 Act, have detailed regard to the
evidence with which the claimant aspires to prove its case. Nonetheless,
because of the complexity of the claims placed before the trial judge
and the nature of the submissions about knowledge in section 14(1) of
the 1980 Act, the trial judge was able to make a "microscopic
survey of the written evidence," especially in respect of
causation. The Court of Appeal had been unusually well-placed in
exercising its discretion under section 33 to assess the claimants'
prospects of establishing causation. Since the Court of Appeal had
concluded that the claimants' faced "very great
difficulties" in establishing causation, and the claimants had no
real prospects of success, it had been correct not to exercise its
discretion to allow the claims to proceed. To have done so would have
been absurd (ibid, Lord Wilson at 100).

(48) Ibid at para 67. As Lord Kerr noted, "[t]he use of the
expression 'single exposure' may be misleading in this
context" (ibid at para 199). It is probably better expressed as
"single tortious exposure cases" (ibid at para 173, Hale B).
These are cases where only one defendant exposed the victim to asbestos
and there was only one possible tortious source for the exposure, and
the only other exposure creating a risk of developing mesothelioma was
environmental exposure to low level asbestos dust in the general
atmosphere (ibid at paras 113, Lord Rodger; 199, Lord Kerr; 207, Lord
Dyson).

(73) Ibid at para 110. This would be the case since "those
applicants who were actually injured by causes other than the
respondent's actionable conduct will be able to recover
compensation because, for them too, a relative risk of greater than 2
can be said to imply probability of greater than 50% that the
respondent's actionable conduct was the cause of their loss"
(ibid). However, this criticism is misconceived, since the problem of
compensation to those not injured by a defendant is generic in any
system that uses a preponderance of the evidence rule and has no
relevance to the type of evidence employed to determine whether the
plaintiff has met the preponderance threshold.

(74) Ibid at para 111. See also Seltsam Pty Ltd v McGuiness, [2000]
NSWCA 29, 49 NSWLR 262, Spigelman CJ (while in Australian law the test
of actual persuasion did not require epidemiological studies to reach
the level of risk of 2.0, "the closer the ratio approaches 2.0, the
greater the significance that can be attached to the studies for the
purposes of drawing an inference of causation in an individual case. The
'strands in the cable' must be capable of bearing the weight
of the ultimate inference" at para 137).

(75) Havner, supra note 10.

(76) Ibid at 718.

(77) Supra note 15 at para 88.

(78) This can be contrasted with the other reason for judicial
scepticism about epidemiological evidence, namely the propriety of
drawing causal inferences from observed associations. It is often
difficult to tease out from the decisions which form of judicial
treatment is taking place.

(81) Ibid. Baroness Hale also opined that "the existence of a
statistically significant association between factor X and disease Y
does not prove that in the individual case it is more likely than not
that factor X caused disease Y" (ibid at para 170). Lord Mance
accepted that epidemiological evidence, used with proper caution, could
be admissible and relevant in conjunction with specific evidence related
to the individual circumstances and parties. The significance a court
might attach to it depended "on the nature of the epidemiological
evidence, and of the particular factual issues before the court"
(ibid at para 191). Lord Kerr considered that "[i]t is an essential
and minimum requirement ... that there be evidence connecting avowedly
relevant statistical information produced by the epidemiological studies
to the facts of the case" (ibid at para 205). Lord Dyson also
stressed the association/causation dichotomy, stating that
"epidemiology ... seeks to establish associations between alleged
causes and effects ... However, in an individual case, epidemiology
alone cannot conclusively prove causation" (ibid at para 218). See
also the recent discussion by the High Court of Australia in Amaca Pty
Ltd v Booth, [2011] HCA 53, 283 ALR 461 at para 49 [Amaca] (where French
CJ distinguished between mere statistical correlation between conduct
and injury and the need to establish causal connection between the
conduct and injury).

(91) Ibid at para 123. Special leave to appeal to the High Court of
Australia was refused since the applications were deemed not suitable
vehicles for the consideration of the relevant questions of principle
that would warrant the grant of leave, "having regard to the
findings of fact of the primary judge and the Full Court's
treatment of them" (Peterson., supra note 17, leave to appeal to
HCA refused, [2012] HCATrans 105).

(92) See McDarby v Merck & Co, 949 A2d 223 at 234 (NJ Super App
Div 2008) [McDarby] (noting that the results of the VIGOR study in March
2000 revealed a higher incidence of adverse cardiovascular events with
those who received rofecoxib (Vioxx) than with those patients who
received naproxen, "in patients with and without a history of
atherosclerotic cardiovascular disease, and in patients with or without
classic risk factors for cardiovascular disease" at 234). See also
Gold, "Revisiting Relative Risk Rules", supra note 29.
Consider the following hypothetical. For those with no pre-existing
heart problems, taking Vioxx raises the risk of heart attacks 101%, more
than doubling the risk from 1% to 2.01%. For those with pre-existing
heart conditions like Peterson, taking Vioxx raises the risk of heart
attacks 101%, from 10% to 20.01%. Vioxx is identically implicated in
both scenarios.

(93) Sir Austin Bradford Hill, "The Environment and Disease:
Association or Causation?" (1965) 58:5 Proceedings of the Royal
Society of Medicine 295 at 295 [Hill, "Association or
Causation"]. These aspects of association (that is, strength of
association, consistency, specificity, temporality, biological gradient,
plausibility, coherence, experiment, and analogy) are utilized to
determine whether a reported association is causal or non-genuine. For
recent support for the Bradford Hill factors as providing a guide to the
kind of considerations that lead to an inference of causal association,
see Amaca, supra note 81 at para 49.

(94) McTear, supra note 16 at para 6.158. However, the presentation
of the list of factors in textbooks as "criteria" for
inferring causality or associations in a way as to imply that all the
conditions are necessary has been described as "unfortunate"
(Sander Greenland, ed, The Evolution of Epidemiologic Ideas: Annotated
Readings on Concepts and Methods (Los Angeles: Epidemiology Resources
Inc, 1987) at 14). As Greenland correctly observes, Sir Austin Bradford
Hill expressly stated that he did not intend to lay down "hard and
fast rules of evidence that must be obeyed before we accept cause and
effect" (ibid, citing Hill, "Association and Causation",
supra note 93 at 299). Hill added that "[n]one of [his] nine
viewpoints can bring indisputable evidence for or against the
cause-and-effect hypothesis and none can be required as a sine qua
non" (ibid at 299 [emphasis in original]). See also Cranor, supra
note 37 at 102-05.

(95) Epidemiology has been defined as "the study of patterns
of disease occurring in human populations and the factors that influence
these patterns" (McTear, supra note 16 at para 6.157).

(96) See ibid at paras 2.58, 2.76, 6.30. This was notwithstanding
the generally accepted view for over 50 years that cigarette smoking
could cause lung cancer (see Richard Doll & A Bradford Hill,
"Smoking and Carcinoma of the Lung: Preliminary Report" [1950]
4682 Brit Med J 739; Richard Doll & A Bradford Hill, "The
Mortality of Doctors in relation to their Smoking Habits: A Preliminary
Report" [1954] 4877 Brit Med J 1451; McTear, supra note 16 at para
5.208 (evidence of Sir Richard Doll)). The defence in McTear admitted
that the World Health Organization, along with United Kingdom and United
States governments, had accepted for years that cigarette smoking can
cause lung cancer. However, they averred that "[c]igarette smoking
has not been scientifically established as a cause of lung cancer and,
although various theories have been advanced, the cause or causes of
lung cancer are unknown and the mechanism or mechanisms whereby lung
cancer develops are unknown" (ibid at para 2.7).

(110) See also United States, the Advisory Committee Note (2000
Amendment) to Fed R Evidence 702. The Amendment not only stresses that
the expert conducts the application of principles and methods to the
facts of cases reliably, but also reiterates the "venerable
practice of using expert testimony to educate the factfinder on general
principles" (ibid). It notes that it might be important in some
cases for an expert to educate the finder of fact about general
principles, without ever attempting to apply these principles to the
specific facts of the case (ibid).

(119) Counsel for the pursuer had submitted (unsuccessfully) that
considerable weight should be placed on the fact that this proposition
had come to be generally accepted (see McTear, supra note 16 at para
6.41).

(120) Ibid at paras 2.7, 6.30.

(121) As Gary Wells has observed, the term "naked statistical
evidence" is ill-defined in the legal literature (see e.g. David
Kaye's use of the term in in David Kaye, "Naked Statistical
Evidence", Book Review of Quantitative Methods in Law: Studies in
the Application of Mathematical Probability and Statistics to Legal
Problems by Michael Finkelstein, (1980) 89:3 Yale LJ 601 at 603; David
Kaye, "The Limits of the Preponderance of the Evidence Standard:
Justifiably Naked Statistical Evidence and Multiple Causation"
(1982) 7:2 Law & Soc Inquiry 487 at 488), though it typically refers
to probabilities that are not case specific to the events in issue
"but rather existed prior to or independently of the particular
case being tried" (Gary L Wells, "Naked Statistical Evidence
of Liability: Is Subjective Probability Enough?" (1992) 62:5
Journal of Personality and Social Psychology 739 at 739).

(122) Timothy Hill, "A Lost Chance for Compensation in the
Tort of Negligence by the House of Lords" (1991) 54:4 Mod L Rev 511
at 512 [Hill, "Lost Chance"].

(136) Hill, "Association or Causation", supra note 93 at
297. The High Court of Australia has recently stressed that reference to
relative risk ratio may act as an indicator of strength of association
(see Amaca, supra note 81 at para 49).

(142) Green, "Epidemiology', supra note 8 at 616, citing
Havner, supra note 10 at 720; see also Smith v Wyeth Ayerst Laboratories
Co, 278 F Supp (2d) 684 at 708-09 (WDNC 2003) (discussing an
expert's attempt to apply principles of relative risk from an
epidemiological study on the relationship between diet drugs and primary
pulmonary hypertension (PPH) to the risk faced by the individual
plaintiff, who developed PPH after taking prescription appetite
suppressants based on specific risk characteristics (duration of use and
timing of use). The expert's opinion was deemed unreliable).

(143) McDarby, supra note 92 at 270.

(144) Ibid at 269-70.

(145) Ibid (applying the substantial factor standard, causation was
appropriately demonstrated by long term use of Vioxx and "medical
and/or scientific proof of a nexus between [that use] and ... plaintiffs
condition" at 271).

(146) Hill, "Lost Chance", supra note 122 at 518.

(147) This builds on the author's discussion in Goldberg,
Causation and Risk in the Law of Torts, supra note 2 at 39-40.

(148) A confounding factor is a factor that is both a risk factor
for the disease and one associated with the exposure in issue.
"Confounding" refers to the situation where an association
between an exposure and an outcome is all or partly due to a factor that
affects the outcome but which is unaffected by the exposure (see Green,
"Epidemiology", supra note 8 at 621).

(150) See Joseph L Gastwirth, "Should Law and Public Policy
Adopt 'Practical Causality' as the Appropriate Criteria for
Deciding Product Liability Cases and Public Policy?" (2013) 12:3
Law, Probability and Risk 169 [Gastwirth, "Practical
Causahty"]; see also Patrick Ryan et al, "Learning from
Epidemiology: Interpreting Observational Database Studies for the
Effects of Medical Products" (2013) 5:3 Statistics in
Biopharmaceutical Research 170 at 178 (supporting a Bayesian framework
to interpret observational database studies for the effects of medical
products and suggesting that future work can extend the Bayesian
framework to include such elements as the Bradford Hill factors).

(151) Frequentist statisticians are those who define probability as
the frequency of a certain measurement or observation. The frequentist
approach focuses on the probability of the data, given the hypothesis.
See Maarten HP Ambaum, "Frequentist vs Bayesian Statistics--A
Non-Statisticians [sic] View" (July 2012), online: Department of
Meteorology, University of Reading, UK
<www.met.reading.ac.uk/~sws97mha/Pubhcations/Bayesvsfreq. pdf>.

(156) See e.g. Neal C Stout & Peter A Valberg,
"Bayes' Law, Sequential Uncertainties, and Evidence of
Causation in Toxic Tort Cases" (2005) 38:4 Mich JL Reform 781 at
787 (submitting that judges should apply Bayesian probabilistic
approaches in toxic tort cases when evaluating the reliability of
medical and scientific evidence, and in so doing permitting the fact
finder to decide only those toxic tort claims for which there is
reliable and relevant scientific support for each link in the causal
chain).

(166) Personal Communication, Professor Philip David, Statistical
Laboratory, Centre for Mathematical Sciences, Cambridge University, 12
July 2013; Robertson and Vignaux advocate that scientific evidence
concerning an issue should be combined with other evidence relating to
the same issue, and that the most effective way of doing so is to
express the evidence in likelihood ratio form for it to be subsequently
combined with other evidence (Robertson & Vignaux, supra note 158 at
220). In addition, they have observed that the likelihood ratio's
importance is that it determines relevance and probative value, the key
determinants of admissibility of expert evidence (ibid at 22). Robertson
and Vignaux have submitted that it is not essential to have precise
numbers for each of the probabilities to assess the likelihood ratio
(ibid). However, this would seem arguable in complex cases involving the
establishment of causation with medicinal products (see Goldberg,
Causation and Risk in the Law of Torts, supra note 2 at 43 n 242).

(169) See also A Philip Dawid, "The Role of Scientific and
Statistical Evidence in Assessing Causality" in Richard Goldberg,
ed, Perspectives on Causation (Oxford: Hart, 2011) 133 at 140-45.

(170) Andersen, supra note 18 at para 1.

(171) Ibid at para 1.

(172) Ibid at para 2.

(173) Ibid at para 1.

(174) Ibid at para 4.

(175) Ibid at para 5.

(176) The reason for the use of the word "material",
which was formulated by Justice Cullity in his certification decision
(ibid at paras 5, 520), was "to ensure that findings with respect
to whether Silzone increases the risk of complications would be
sufficiently meaningful that they would be indicative of something more
than a remote possibility of causation" (ibid at para 528).

(177) XYZ, supra note 40 at paras 20-21.

(178) See Andersen, supra note 18 at paras 6,182-83, 214.

(179) See ibid at para 384.

(180) Ibid.

(181) See ibid at para 395.

(182) See ibid at paras 532-38. The arithmetical explanation for
adopting the "doubling of risk" rule (ibid at paras 532-34) is
almost identical to that provided in XYZ, supra note 40 at para 21.

(188) Cranor, supra note 37 at 366; see also ibid at 289-90, 335.
Courts should not exclude causal opinions based on non-epidemiological
evidence where a body of epidemiological data does not exist (David L
Faigman et al, "How Good is Good Enough?: Expert Evidence Under
Daubert and Kumho" (2000) 50:3 Case W Res L Rev 645 at 663).

(189) For support for a probabilistic model of specific causation
in toxic torts, when the dominating evidence comprises population-based
data of the toxic effect, see especially Gold, "Certainty
Dissolves", supra note 130 at 281, 303-04, 338-39.

(192) See Cranor, supra note 37 at 256-59. For further discussion
of the National Childhood Vaccine Injury Compensation Program, see
Goldberg, Causation and Risk in the Law of Torts, supra note 2 at
163-70.

(193) Feldschreiber, Mulcahy, and Day provide a good illustration
of the failure to take account of absolute risk: "If there is an
incidence of disease in an unexposed population of one in a million
cases and in an exposed population of two in a million cases, the RR is
two but the absolute risk is very low" (Feldschreiber, Mulcahy
& Day, supra note 19 at 188). The Federal Full Court of Australia
observe in Peterson that "[d]oubling a very low absolute risk of an
adverse result may produce an absolute risk which itself remains so low
that a positive finding of causation on the balance of probabilities
would itself be an affront to common sense" (supra note 17 at para
119). However, I respectfully submit that as a matter of statistics,
this observation is incorrect. If one accepts the premise of this paper
that population-based estimates are relevant to causal conclusions in
individual cases, then doubling of risk is doubling of risk,
irrespective of absolute risk. One can concede the intuitive appeal of
the court's statement. Thus, if in a population of 100 million
unexposed individuals, only one case of disease were expected, who could
submit that finding two cases represented anything other than a fluke?
However, that intuition is merely an illustration of the difficulty in
obtaining statistically significant results in the epidemiological
investigation of rare conditions. If there were a way of designing an
epidemiological study of sufficient quality, capable of identifying an
association that truly exists (i.e., one with sufficient power), it
could be said with great confidence that the exposure (generally) causes
the disease. I am grateful to an anonymous reviewer for this point.

Richard Goldberg, Professor of Law, Durham University, UK. Earlier
drafts of this paper were delivered to the Department of Epidemiology,
Biostatistics and Occupational Health, Faculty of Medicine, McGill
University, Montreal, April 2011 under a Carnegie Research Grant, and to
the first meeting of the Technological Innovations, Uncertainty, and
Responsibility network, Faculty of Law, McGill University, 5 July 2012.
The author wishes to thank Professors Philip Dawid and David Goldberg
for helpful discussions.

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